Dataset Information

Resource allocation for mitigating regional air pollution-related mortality: A summertime case study for five cities in the United States.

ABSTRACT:

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An important issue of regional air quality management is to allocate air quality management funds to maximize environmental and human health benefits. In this study, we use an innovative approach to tackle this air quality management issue. We develop an innovative resource allocation model that allows identification of air pollutant emission control strategies that maximize mortality avoidances subject to a resource constraint. We first present the development of the resource allocation model and then a case study to show how the model can be used to identify resource allocation strategies that maximize mortality avoidances for top five Metropolitan Statistical Areas (MSAs) (i.e., New York, Los Angeles, Chicago, Dallas-Fort Worth, and Philadelphia) in the continental United States collectively. Given budget constraints in the U.S. Environmental Protection Agency's (EPA) Clean Air Act assessment, the results of the case study suggest that controls of sulfur dioxide (SO2) and primary carbon (PC) emissions from EPA Regions 2, 3, 5, 6, and 9 would have significant health benefits for the five selected cities collectively. Around 30,800 air pollution-related mortalities could be avoided during the selected 2-week summertime episode for the five cities collectively if the budget could be allocated based on the results of the resource allocation model. Although only five U.S. cities during a 2-week episode are considered in the case study, the resource allocation model can be used by decision-makers to plan air pollution mitigation strategies to achieve the most significant health benefits for other seasons and more cities over a region or the continental U.S.

Implications

Effective allocations of air quality management resources are challenging and complicated, and it is desired to have a tool that can help decision-makers better allocate the funds to maximize health benefits of air pollution mitigation. An innovative resource allocation model developed in this study can help decision-makers identify the best resource allocation strategies for multiple cities collectively. The results of a case study suggest that controls of primary carbon and sulfur dioxides emissions would achieve the most significant health benefits for five selected cities collectively.

SUBMITTER: Liao KJ

PROVIDER: S-EPMC4960509 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Publications

Resource allocation for mitigating regional air pollution-related mortality: A summertime case study for five cities in the United States.

Liao Kuo-Jen KJ Hou Xiangting X Strickland Matthew J MJ

Journal of the Air & Waste Management Association (1995) 20160801 8

<h4>Unlabelled</h4>An important issue of regional air quality management is to allocate air quality management funds to maximize environmental and human health benefits. In this study, we use an innovative approach to tackle this air quality management issue. We develop an innovative resource allocation model that allows identification of air pollutant emission control strategies that maximize mortality avoidances subject to a resource constraint. We first present the development of the resource ...[more]

PMID: 27441782

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Project description:Nowadays, innovation seems to be the inevitable choice to achieve stable economic growth. However, the negative impact of air pollution on health and economy makes air pollution an important factor in regional innovation, which deserves our discussion. The overall regional innovation level from 2014 to 2019 has an upward trend, while the overall air pollution has a downward trend during the period, which provides foundation for our research. Based on the data of 285 prefecture-level cities in China from 2014 to 2019, this paper uses the fixed effect and mediation model to verify the impact and mechanism of air pollution on regional innovation. The results show that the increase in air pollution, measured by the air quality index, significantly inhibits regional innovation. Air pollution has significant funds crowding-out effect and human capital loss effect, thereby decreasing the regional innovation level, which means innovation funds and researchers play a conductive role between air pollution and regional innovation. In heterogeneity analysis, it is found that the detrimental effect of air pollution on regional innovation is significant in eastern and central China, in large- and medium-sized cities, and in cities with poor or general air quality. It indicates that developed and large-scale regions should pay more attention to air pollution control. For polluted regions, more emphasis and endeavors are needed to address air pollution problems. Besides, the inhibitory effect is more severe on incremental innovation rather than on radical innovation, which deserves the attention of enterprises engaged in incremental innovation. Therefore, we propose that targeted environmental policies and effective measures should be developed to improve air quality in the long run. Moreover, policymakers could provide strong support for innovation grants, talent subsidies, and rewards and encourage clean technological innovation through short-term trade-offs between heavily polluting and low polluting enterprises.

Project description:BackgroundThe systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias.MethodsWe evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 ?m or less (PM10) and fine PM with an aerodynamic diameter of 2.5 ?m or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived.ResultsOn average, an increase of 10 ?g per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations.ConclusionsOur data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).

Dataset Information

Resource allocation for mitigating regional air pollution-related mortality: A summertime case study for five cities in the United States.

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Implications

Publications

Resource allocation for mitigating regional air pollution-related mortality: A summertime case study for five cities in the United States.

Similar Datasets

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